Tools for preprocessing data and training LSTM models to reconstruct streamflow at ungaged upstream locations of CAMELS basins using CAMELS gage data and inputs from the NWM 3.0 retrospective dataset.

2 Open Issues Need Help Last updated: Jun 24, 2025

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Hydrology Streamflow Modeling

AI Summary: Investigate the discrepancy between the expected 672 CAMELS basins and the 639 basins with data in the `s3://camels-nwm-reanalysis` bucket. Determine why 33 basins are missing. This involves analyzing the provided `camels_link.csv` and `camels_upstream_dict.json` files, potentially examining the data processing steps (01.01 and 01.02) described in the project README. The goal is either to generate the missing data or document a justified reason for their absence, acknowledging limitations in the `RouteLink` file.

Complexity: 4/5
bug documentation help wanted good first issue

Tools for preprocessing data and training LSTM models to reconstruct streamflow at ungaged upstream locations of CAMELS basins using CAMELS gage data and inputs from the NWM 3.0 retrospective dataset.

Python
Hydrology Streamflow Modeling

AI Summary: Create a script to preprocess hydrological data. Given a downstream CAMELS basin and a specified upstream distance (n), the script should average meteorological forcing data from multiple upstream subbasins and extract streamflow data for both the downstream and selected upstream basin, saving the results into a new NetCDF file. The script should handle data retrieval from an S3 bucket and potentially utilize multiprocessing for efficiency.

Complexity: 4/5
enhancement good first issue

Tools for preprocessing data and training LSTM models to reconstruct streamflow at ungaged upstream locations of CAMELS basins using CAMELS gage data and inputs from the NWM 3.0 retrospective dataset.

Python